# Meta Content / Social-Listening Intel - Facebook + Instagram (`seibs.co/meta-content-intel`) Actor Public-post social listening across Facebook + Instagram: search by keyword/hashtag/page; capture post text, engagement, and timestamps; get topic volume, sentiment, themes, and share-of-voice. The commercial alternative to Meta Content Library (academic-only). For brands, PR, and agencies. - **URL**: https://apify.com/seibs.co/meta-content-intel.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** Business, Marketing, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 1,000 public post records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Meta Content / Social-Listening Intel - Facebook + Instagram **Public-post social listening across Facebook + Instagram public Pages/posts.** Search public posts by keyword/topic/hashtag/page, capture post text, engagement, timestamps, and the public author, then get the social-listening intelligence that matters: **topic volume over time, sentiment + themes, top posts/pages, and cross-topic share-of-voice** - in one normalized schema. This is the commercial answer to a gated API. Meta's official social-listening path - the **Meta Content Library** (CrowdTangle's successor) - is **application-restricted to academic and non-profit researchers**. Brands, PR/comms teams, agencies, and journalists are categorically excluded. This actor delivers the equivalent public-post listening data from the logged-out public surface, **no application required**. > **Scope - read this first.** This actor is *organic public-post social > listening*. It is deliberately distinct from two sibling actors: > - It is **NOT** [ad-library-intel](https://apify.com/seibs.co/ad-library-intel) - that covers paid **ads** from the ad-transparency archives. > - It is **NOT** instagram-creator-intel - that covers **creator / influencer** audience analytics. > If you want ads, use ad-library-intel. If you want creator metrics, use the creator actor. If you want to listen to what's being said about a topic/brand in public posts, you're in the right place. --- ### What you get A single dataset stream of normalized records, keyed by `record_type`: | record_type | What it is | |---|---| | `post` | One normalized public post: platform, public author, post type, text, engagement (likes/comments/shares/views), timestamp, hashtags, mentions, media URLs, permalink. | | `topic_rollup` | Per-topic aggregation: post volume over time, sentiment split, top posts, top pages, top hashtags. | | `share_of_voice` | Cross-topic table: each topic/brand's share of posts + engagement and its sentiment split. | | `access_notes` | Per-platform access method, anti-bot escalation telemetry, PII posture, and responsible-use note. | | `platform_pending` / `fetch_error` | Honest fail-soft notes when a logged-out surface was blocked (Meta login-walls automated clients). Never fabricated data. | | `monitor_digest` | On scheduled runs: new posts + volume/sentiment shift since the last run. | Five dataset **views** are pre-defined: `overview` (AI-agent / analyst skim), `posts` (every field), `topics` (rollups), an MCP-compatible JSON link, and a CSV download. --- ### Modes | Mode | Input | Does | |---|---|---| | `keyword_listening` (default) | `keywords` | Search public posts by topic across platforms, then aggregate (volume, sentiment, top posts/pages, share-of-voice). | | `page_posts` | `pages` | Pull recent public posts for given Facebook Pages / public Instagram profiles (brand/competitor owned content). | | `hashtag_intel` | `hashtags` | Pull public hashtag feeds + topic-volume / top-posts intel. | **Note on keyword search:** Facebook and Instagram have **no logged-out keyword *post* search** (their search UIs require login). In `keyword_listening` mode a keyword is therefore matched against its **hashtag feed** on each platform - the closest public, logged-out equivalent. For owned-content monitoring use `page_posts`. #### Example input ```json { "mode": "keyword_listening", "keywords": ["sustainability", "plant based"], "platforms": ["facebook", "instagram"], "max_results_per_platform": 30, "include_listening_analysis": true, "include_topic_rollup": true, "pii_minimization": true } ```` *** ### Legal-safety & responsible use This actor follows the portfolio's gated-data playbook (Section B): - **Logged-out, public-only.** No login, no account, no user cookies, no paid token. Only public Pages/posts and public profiles/hashtag feeds. - **PII minimization (on by default).** Posts authored by an apparent *personal individual* (not a Page / business / verified account) have the author name dropped and the handle replaced with a stable opaque token (`person_xxxx`), and the author id stripped. Pages/business/verified accounts (the brands and orgs social listening is about) are retained. The dataset is about **public discourse on a topic, not a profile of private individuals.** Turn off only with a lawful basis (`pii_minimization=false`). - **Polite rate limits** and bounded concurrency. - **Fail-soft.** When a surface blocks the logged-out request, the actor emits a documented `platform_pending` note - it never fabricates data. - **Favorable precedent.** *Meta v. Bright Data (2024)* held that logged-off scraping of public Meta data is not barred by Meta's terms. Use this for aggregate brand/topic listening, reputation monitoring, PR/comms, and trend research - not for surveillance of individuals. *** ### Anti-bot escalation Meta's public surfaces are token-gated and login-wall automated clients. The actor runs a four-tier ladder per request: 1. **httpx** over the DATACENTER proxy (cheapest, first). 2. **curl\_cffi** with real Chrome TLS impersonation over the RESIDENTIAL proxy (defeats JA3/TLS fingerprinting). 3. **patchright / playwright** stealth browser over the RESIDENTIAL proxy - loads the public page and replays its own JSON XHR (Instagram `web_profile_info` / `tags/web_info`; Facebook GraphQL). Runs on the `apify/actor-python-playwright` base image (headful under Xvfb). 4. **Fail-soft** - a documented `platform_pending` / `fetch_error` note. For the most reliable results against managed challenges, point `browser_cdp_url` (or the `BROWSER_CDP_URL` env var) at a warm anti-detect browser; the browser tier connects over CDP and inherits its session + IP. *** ### Pricing (pay-per-event) | Event | Price | What | |---|---|---| | `post_record` | $0.004 | One normalized public post. | | `listening_analysis` | $0.008 | Sentiment + theme tagging per post. | | `topic_rollup` | $0.010 | Per-topic volume/sentiment/top-posts/SOV aggregation. | | `scheduled_delta_run` | $0.050 | One monitor-mode delta digest. | **A run that returns nothing costs nothing.** A 5-layer cost-control defense (pre-flight caps, demo-mode soft-fail, `_RunBudget` guard, in-loop budget checks, hardcoded prices) protects against runaway compute. *** ### Monitor mode Save your input as a task and put it on an [Apify Schedule](https://console.apify.com/schedules). On scheduled runs the actor compares against the previous run and emits a `monitor_digest` (new posts, volume + sentiment shift). Set `monitor_webhook_url` to post the digest to a Slack-compatible webhook. *** ### MCP / AI-agent use An MCP twin, **mcp-meta-content-intel**, exposes this actor as AI-agent tools (`search_public_posts`, `get_page_posts`, `get_hashtag_posts`, `analyze_topic`, `track_topic_mentions`) and is x402 (USDC on Base) + Skyfire ready for token-less agentic payments. Or wire the `overview` view directly via the MCP-compatible dataset link in the output. *** ### Who it's for Brands and DTC companies monitoring their reputation, PR/comms teams tracking narrative and sentiment, agencies running social-listening for clients, journalists and researchers studying public discourse - everyone locked out of Meta Content Library's academic-only gate. # Actor input Schema ## `mode` (type: `string`): keyword\_listening = search public posts by keyword/topic across platforms, then aggregate (volume, sentiment, top posts/pages, share-of-voice). page\_posts = pull recent public posts for given Facebook Pages / public Instagram profiles. hashtag\_intel = public hashtag feeds + topic intel. ## `keywords` (type: `array`): Topics/terms to listen for, e.g. \['climate change', 'your brand']. Used in keyword\_listening mode. Note: Facebook and Instagram have no logged-out keyword post-search, so a keyword is matched against its hashtag feed. Hard cap of 25. ## `pages` (type: `array`): Facebook Page names/slugs or public Instagram handles to pull recent public posts for, e.g. \['natgeo', 'nike', 'patagonia']. Used in page\_posts mode. Hard cap of 50. ## `hashtags` (type: `array`): Hashtags (without the #) to pull public feeds for, e.g. \['sustainability', 'running']. Used in hashtag\_intel mode. Hard cap of 25. ## `platforms` (type: `array`): Which Meta surfaces to listen to: facebook (public Pages + hashtags), instagram (public profiles + hashtags). Aliases like 'fb', 'ig', 'meta' are accepted. Leave empty for both. Pass \['all'] for both. ## `all_platforms` (type: `boolean`): Shortcut to query Facebook + Instagram (overrides the platforms list). ## `country` (type: `string`): Two-letter region code used as a soft locale hint where the surface honors it (e.g. US, GB, DE). Default US. ## `include_listening_analysis` (type: `boolean`): Tag each post's sentiment (positive / negative / neutral, lexicon-based), theme (praise / complaint / question / recommendation / news / promotion), hashtags, and emoji/word count. Adds a listening\_analysis PPE charge per tagged post. This is the social-listening corpus signal. ## `include_topic_rollup` (type: `boolean`): Build per-topic aggregations: post volume over time, sentiment split, top posts, top pages, top hashtags, plus the cross-topic share-of-voice table. Adds a topic\_rollup PPE charge per topic. Defaults on for keyword\_listening and hashtag\_intel. ## `pii_minimization` (type: `boolean`): When on (default), posts authored by an apparent personal individual (not a Page / business / verified account) have the author name dropped and the handle replaced with a stable opaque token, and the author id is stripped. Pages/business/verified accounts are retained. Keeps the dataset about public discourse on a topic, not a profile of private individuals. Turn off only with a lawful basis. ## `max_results_per_platform` (type: `integer`): Hard cap on posts returned per platform per keyword/page/hashtag. Default 30. ## `monitor_webhook_url` (type: `string`): When this actor runs under an Apify Schedule (monitor mode), post the change digest (new posts, volume/sentiment shift) to this Slack-compatible webhook URL. ## `use_apify_proxy` (type: `boolean`): Route requests through Apify Proxy. DATACENTER handles the first (httpx) pass; a RESIDENTIAL tier is provisioned for the anti-bot escalation legs (Meta's public surfaces usually need residential to clear logged-out). ## `use_browser_fallback` (type: `boolean`): When a surface serves an anti-bot / login wall (Facebook and Instagram heavily gate logged-out automated clients), automatically escalate: switch to the RESIDENTIAL proxy and retry with curl\_cffi Chrome TLS impersonation, then a stealth browser that replays the page's own JSON XHR. Turn off to use plain httpx only (Meta then returns documented platform\_pending notes). ## `browser_cdp_url` (type: `string`): Optional. CDP/WebSocket endpoint of an already-running, anti-detect (UC-mode / real Chrome) browser. When set, the browser tier connects to it (inheriting its session + fingerprint) so it clears Meta's edge more reliably. Without it a stealth headless Chromium is launched (works on the apify/actor-python-playwright image; weaker against managed challenges). Can also be set as the BROWSER\_CDP\_URL env var. ## `apify_proxy_groups` (type: `array`): Override the auto-selected proxy group. Leave empty to let the actor pick DATACENTER for the first pass and RESIDENTIAL for escalation. ## `concurrency` (type: `integer`): Parallel surface fetches. Meta's surfaces are rate-sensitive; default 4. ## Actor input object example ```json { "mode": "keyword_listening", "keywords": [ "sustainability", "plant based" ], "pages": [], "hashtags": [], "platforms": [ "facebook", "instagram" ], "all_platforms": false, "country": "US", "include_listening_analysis": true, "include_topic_rollup": true, "pii_minimization": true, "max_results_per_platform": 20, "monitor_webhook_url": "", "use_apify_proxy": true, "use_browser_fallback": true, "browser_cdp_url": "", "apify_proxy_groups": [], "concurrency": 4 } ``` # Actor output Schema ## `datasetItems` (type: `string`): Narrow, token-efficient slice of every record. Consumer: LLM agents (Claude, GPT, LangChain tools), MCP hosts, dashboards. Fields: platform, author, post type, sentiment, engagement, posted date, permalink. ## `datasetItemsPosts` (type: `string`): All fields for every public post. Consumer: humans browsing the dataset, RAG ingest, full backups. Larger payload - not recommended as a direct LLM tool response. ## `datasetItemsTopics` (type: `string`): Per-topic aggregations (volume over time, sentiment split, top posts/pages/hashtags). Consumer: social-listening dashboards, PR/comms reporting. ## `datasetItemsMcp` (type: `string`): First 50 overview records as a clean JSON array. Wrap on the agent side in an MCP tool-call response envelope, e.g. `{ "ok": true, "data": , "meta": { "actor": "meta-content-intel", "count": , "view": "overview" } }`. Consumer: MCP servers, Claude Desktop, Cursor, OpenAI Assistants tool calls. ## `datasetItemsCsv` (type: `string`): Spreadsheet-friendly export of the overview view. Consumer: humans, marketing/comms teams, Excel / Google Sheets users. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "mode": "keyword_listening", "keywords": [ "sustainability", "plant based" ], "platforms": [ "facebook", "instagram" ], "country": "US", "max_results_per_platform": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/meta-content-intel").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "mode": "keyword_listening", "keywords": [ "sustainability", "plant based", ], "platforms": [ "facebook", "instagram", ], "country": "US", "max_results_per_platform": 20, } # Run the Actor and wait for it to finish run = client.actor("seibs.co/meta-content-intel").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "mode": "keyword_listening", "keywords": [ "sustainability", "plant based" ], "platforms": [ "facebook", "instagram" ], "country": "US", "max_results_per_platform": 20 }' | apify call seibs.co/meta-content-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/meta-content-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Meta Content / Social-Listening Intel - Facebook + Instagram", "description": "Public-post social listening across Facebook + Instagram: search by keyword/hashtag/page; capture post text, engagement, and timestamps; get topic volume, sentiment, themes, and share-of-voice. The commercial alternative to Meta Content Library (academic-only). For brands, PR, and agencies.", "version": "0.1", "x-build-id": "jxZK34QVLBqbzKweV" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~meta-content-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-meta-content-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seibs.co~meta-content-intel/runs": { "post": { "operationId": "runs-sync-seibs.co-meta-content-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seibs.co~meta-content-intel/run-sync": { "post": { "operationId": "run-sync-seibs.co-meta-content-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "keyword_listening", "page_posts", "hashtag_intel" ], "type": "string", "description": "keyword_listening = search public posts by keyword/topic across platforms, then aggregate (volume, sentiment, top posts/pages, share-of-voice). page_posts = pull recent public posts for given Facebook Pages / public Instagram profiles. hashtag_intel = public hashtag feeds + topic intel.", "default": "keyword_listening" }, "keywords": { "title": "Keywords / topics (keyword_listening mode)", "maxItems": 25, "type": "array", "description": "Topics/terms to listen for, e.g. ['climate change', 'your brand']. Used in keyword_listening mode. Note: Facebook and Instagram have no logged-out keyword post-search, so a keyword is matched against its hashtag feed. Hard cap of 25.", "default": [], "items": { "type": "string" } }, "pages": { "title": "Pages / profiles (page_posts mode)", "maxItems": 50, "type": "array", "description": "Facebook Page names/slugs or public Instagram handles to pull recent public posts for, e.g. ['natgeo', 'nike', 'patagonia']. Used in page_posts mode. Hard cap of 50.", "default": [], "items": { "type": "string" } }, "hashtags": { "title": "Hashtags (hashtag_intel mode)", "maxItems": 25, "type": "array", "description": "Hashtags (without the #) to pull public feeds for, e.g. ['sustainability', 'running']. Used in hashtag_intel mode. Hard cap of 25.", "default": [], "items": { "type": "string" } }, "platforms": { "title": "Platforms", "maxItems": 2, "uniqueItems": true, "type": "array", "description": "Which Meta surfaces to listen to: facebook (public Pages + hashtags), instagram (public profiles + hashtags). Aliases like 'fb', 'ig', 'meta' are accepted. Leave empty for both. Pass ['all'] for both.", "items": { "type": "string", "enum": [ "facebook", "instagram" ] }, "default": [ "facebook", "instagram" ] }, "all_platforms": { "title": "Query all platforms", "type": "boolean", "description": "Shortcut to query Facebook + Instagram (overrides the platforms list).", "default": false }, "country": { "title": "Country / region", "type": "string", "description": "Two-letter region code used as a soft locale hint where the surface honors it (e.g. US, GB, DE). Default US.", "default": "US" }, "include_listening_analysis": { "title": "Listening analysis (sentiment + theme tagging)", "type": "boolean", "description": "Tag each post's sentiment (positive / negative / neutral, lexicon-based), theme (praise / complaint / question / recommendation / news / promotion), hashtags, and emoji/word count. Adds a listening_analysis PPE charge per tagged post. This is the social-listening corpus signal.", "default": true }, "include_topic_rollup": { "title": "Topic rollups + share-of-voice", "type": "boolean", "description": "Build per-topic aggregations: post volume over time, sentiment split, top posts, top pages, top hashtags, plus the cross-topic share-of-voice table. Adds a topic_rollup PPE charge per topic. Defaults on for keyword_listening and hashtag_intel.", "default": true }, "pii_minimization": { "title": "PII minimization (redact personal individuals)", "type": "boolean", "description": "When on (default), posts authored by an apparent personal individual (not a Page / business / verified account) have the author name dropped and the handle replaced with a stable opaque token, and the author id is stripped. Pages/business/verified accounts are retained. Keeps the dataset about public discourse on a topic, not a profile of private individuals. Turn off only with a lawful basis.", "default": true }, "max_results_per_platform": { "title": "Max posts per platform per query", "minimum": 1, "maximum": 200, "type": "integer", "description": "Hard cap on posts returned per platform per keyword/page/hashtag. Default 30.", "default": 30 }, "monitor_webhook_url": { "title": "Monitor webhook URL (Slack / email, optional)", "type": "string", "description": "When this actor runs under an Apify Schedule (monitor mode), post the change digest (new posts, volume/sentiment shift) to this Slack-compatible webhook URL.", "default": "" }, "use_apify_proxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route requests through Apify Proxy. DATACENTER handles the first (httpx) pass; a RESIDENTIAL tier is provisioned for the anti-bot escalation legs (Meta's public surfaces usually need residential to clear logged-out).", "default": true }, "use_browser_fallback": { "title": "Anti-bot escalation (curl_cffi + browser)", "type": "boolean", "description": "When a surface serves an anti-bot / login wall (Facebook and Instagram heavily gate logged-out automated clients), automatically escalate: switch to the RESIDENTIAL proxy and retry with curl_cffi Chrome TLS impersonation, then a stealth browser that replays the page's own JSON XHR. Turn off to use plain httpx only (Meta then returns documented platform_pending notes).", "default": true }, "browser_cdp_url": { "title": "Warm browser CDP endpoint (for login-walled surfaces)", "type": "string", "description": "Optional. CDP/WebSocket endpoint of an already-running, anti-detect (UC-mode / real Chrome) browser. When set, the browser tier connects to it (inheriting its session + fingerprint) so it clears Meta's edge more reliably. Without it a stealth headless Chromium is launched (works on the apify/actor-python-playwright image; weaker against managed challenges). Can also be set as the BROWSER_CDP_URL env var.", "default": "" }, "apify_proxy_groups": { "title": "Proxy groups (optional override)", "type": "array", "description": "Override the auto-selected proxy group. Leave empty to let the actor pick DATACENTER for the first pass and RESIDENTIAL for escalation.", "default": [], "items": { "type": "string" } }, "concurrency": { "title": "Max concurrent requests", "minimum": 1, "maximum": 8, "type": "integer", "description": "Parallel surface fetches. Meta's surfaces are rate-sensitive; default 4.", "default": 4 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```